Small herbaria contribute unique biogeographic records to county, locality, and temporal scales

Abstract

With digitization and data sharing initiatives underway over the last 15 years, an important need has been prioritizing specimens to digitize. Because duplicate specimens are shared among herbaria in exchange and gift programs, we investigated the extent to which unique biogeographic data are held in small herbaria vs. these data being redundant with those held by larger institutions. We evaluated the unique specimen contributions that small herbaria make to biogeographic understanding at county, locality, and temporal scales. METHODS: We sampled herbarium specimens of 40 plant taxa from each of eight states of the United States of America in four broad status categories: extremely rare, very rare, common native, and introduced. We gathered geographic information from specimens held by large (≥100,000 specimens) and small (<100,000 specimens) herbaria. We built generalized linear mixed models to assess which features of the collections may best predict unique contributions of herbaria and used an Akaike information criterion-based information-theoretic approach for our model selection to choose the best model for each scale. RESULTS: Small herbaria contributed unique specimens at all scales in proportion with their contribution of specimens to our data set. The best models for all scales were the full models that included the factors of species status and herbarium size when accounting for state as a random variable. CONCLUSIONS: We demonstrated that small herbaria contribute unique information for research. It is clear that unique contributions cannot be predicted based on herbarium size alone. We must prioritize digitization and data sharing from herbaria of all sizes.

Ancient woodland indicator species: can old herbarium specimens supplement recent records to inform ecological management?

“…Two of the three highest contributors of old AWI specimens were small collections with a regional focus; Gloucester City Museum and the Royal Agricultural University. Small herbaria (<100,000 specimens (Lavoie 2013)) have been well-recognised in the literature for their contribution to biodiversity data (Colombo et al 2016;Marsico et al 2020) and the results reinforce that such collections should not be overlooked.…”

How does spatial extent and environmental limits affect the accuracy of species richness estimates from ecological niche models? A case study with North American Pinaceae and Cactaceae

“…Models trained with larger presence datasets tend to perform better due to improved sampling of environmental tolerances of species and reduced sampling bias (Araújo & Guisan, 2006; Stockwell & Peterson, 2002). Occurrence data are rapidly being digitized and disseminated online (Reginato & Michelangeli, 2020; Zurell, Franklin, et al, 2020; Petersen et al, 2021), but the records are available for a small percentage of existing specimens, which may themselves represent a fraction of global plant diversity (Marsico et al, 2020). Additionally, collections are often reduced to plants that are easy to acquire due to their accessible locations (Elith & Leathwick, 2009; Kadmon et al, 2004) whereas factors such as difficulty of handling and preserving cacti specimens (Baker et al, 1985; Fosberg, 1932) or narrow endemism and rarity (Ferrier & Guisan, 2006; Papeş & Gaubert, 2007) may limit collecting efforts.…”

Herbarium records reveal multiple phases in the relationship between minimum residence time and invasion ranges of alien plant species

“…That being said, the recording time lags would not influence our main conclusions, although the ‘true’ lag phase might be longer than our modelling estimates. Furthermore, some species with restricted ranges or small population sizes could be absent from herbarium records, because of imperfect detection, incomplete or inaccurate records and limited communication amongst jurisdictions and collections (e.g., Marsico et al, 2020; Nic Lughadha et al, 2019). Defining species ranges is thus affected by various sources of bias, both spatially and temporally.…”